The biotechnology industry is strongly motivated to develop high performance processes in a minimal time frame to meet increasing market demands and reduce manufacturing costs. Many efforts have focused on media optimization, since a well-balanced media composition is essential for two major elements of a fed-batch process: maximal viable cell density and productivity. See Jerums and Yang (2005) BioProcess International, 3:38-44; Zhang et al. (2008) BioPharm International, 21:60-8; Hodge (2005) BioPharm. International., 18:1-4; and Li, F. et al. (2010) mAbs, 2:455-477.
Process development for protein therapeutics is increasingly dependent on high-throughput (HT) technologies to accelerate the screening of many conditions and the optimization of cell culture process outputs. Automated HT experimentation provides opportunities to explore a large design space by using full factorial experimental design and to decrease costs by reducing raw materials, culture media, labor and time. See Amanullah, A. et al. (2010) Biotechnol. Bioeng., 106:57-67; Bareither, R. and Pollard, D. (2011) Biotechnol. Prog, 27:2-14; and Barrett, T. A. et al. (2010) Biotechnol. Bioeng., 105:260-75. Among the numerous HT systems available, microwell plates, which were first used for analytical applications, have become an important tool for microbial and mammalian cell culture applications during the last ten years. Intense efforts were made to understand suspension culture conditions within these devices, by characterizing oxygen mass transfer rates and mixing conditions in particular, to confirm their efficiency in supporting cell culture needs. Their integration into standard lab automation liquid handling platforms that enable simultaneous loading, sampling and feeding of cells, and the incorporation of fluorescence patch sensors into wells to perform pH, dissolved oxygen (DO), and optical density (OD) measurements, have made them an efficient scale-down tool for bioprocess development studies. See Baboo et al. (2012) Biotechnol. Prog., 28:392-405; Chen, A. et al. (2009) Biotechnol. Bioeng., 102:148-60; Duetz, W. A. (2007) Trends Microbiol., 15:469-75; Funke, M. et al. (2009) Biotechnol. Bioeng, 103:1118-28; Micheletti, M. and Lye, G. J. (2006) Curr. Opin. Biotechnol., 17:611-618; and Wen Y et al. (2012) Process Biochem., 47:612-618.
Medium optimization is an important step in process development as medium components at suboptimal concentrations might be limiting for cell growth or productivity, and therefore might directly affect process performance. See Kim, D. Y. et al. (2005) Cytotechnol., 47:37-49. On the other hand, medium components might also have an effect on secreted proteins, more particularly on their glycosylation, which is essential for their bioactivity and stability in vivo. See Gawlitzek, M. et al. (2009) Biotechnol. Bioeng., 103:1164-1175; and Hossler, P. et al. (2009) Glycobiology, 19:936-49. The traditional strategy used for culture medium development relies on the variation of one factor at a time (OFAT) while keeping the others constant. This is laborious, time-consuming, and does not account for synergistic interactions of components. Therefore, new technologies and methods involving design of experiments (DoE) and statistical analysis have been implemented.
These DoE and statistical analysis technologies enable the testing of several components at a time and identification of their interactions. See Lee, G. M. et al. (1999) J. Biotechnol., 69:85-93; Sandadi, S. et al. (2006) Biotechnol. Prog., 22:595-600; and Zhang, H. et al. (2012) Cytotechnol. published online 21 Aug. 2012. Several strategies for medium optimization have been described. See Jerums, M. and Yang, X. (2005); Zhang, M. et al. (2008). For example, optimization can be based on spent medium analysis, see Xie, L. and Wang, D. I. (1994) Biotechnol Bioeng, 43:1164-74. Optimization can also be based on metabolite flux analyses or on metabolomics, which allow rebalance of components in subsequent experiments, see Dietmair, S. et al. (2012) Biotechnol. Bioeng., 109:1404-14; Selvarasu, S. et al. (2012) Biotechnol. Bioeng., 109:1415-1429; and Xing, Z. et al. (2011) Process Biochem., 46:1423-1429. On the other hand, in the high-throughput approach where statistical DoE is linked to automation and small cell culture devices, enable testing of several hundreds of media formulations, tests are usually performed by monitoring critical process outputs (e.g., cell growth, protein titers). This enables testing of several hundreds of media formulations, See Barrett et al. (2010); Didier, C. et al. (2007) Chemom. Intell. Lab. Syst., 86:1-9; Girard, P. et al. (2001) Biochem. Eng. J., 7:117-119; and Hodge, G. (2005) Biopharm International, 18:1-4.
When working with complex biological systems such as recombinant mammalian cell cultures, mixture designs to evaluate combinations of different defined formulations can be an important tool for media optimization. See Jerums and Yang (2005); Didier et al. (2007); and Rispoli, F. and Shah, V. (2009) Biotechnol. Prog., 25:980-985. This approach is particularly interesting when testing numerous components because it avoids component solubility issues that might occur using factorial designs. Optimal concentration ranges of the various culture medium components can be identified by evaluating the performance of the various new mixtures obtained by media blending. Jordan et al. recently described a novel high-throughput method based on an extended media blending strategy that was used to reshuffle 20 amino acids in one round of experiments. See Jordan, M. et al. (2013) Cytotechnol., 65:31-40. Several significantly improved viable cell densities and titers of a Chinese hamster ovary (CHO) cell batch culture producing a monoclonal antibody (mAb) resulted from 192 mixtures prepared by media blending from 10 formulations.
Usually, medium and feed development of a fed-batch process are performed sequentially because of the large number of experiments required for a simultaneous optimization. For example, Zhang et al. (2012) sequentially developed a medium and a feed for a fed-batch process for CHO cells expressing a recombinant antibody. Zhang et al. used a Plackett-Burman design to screen active factors for cell growth and antibody production, followed by a central composite design to optimize their concentration, and by a feeding design based on stoichiometric ratios of different nutrients improving productivity. Nevertheless, the outcome of a successive optimization strategy might not always be ideal because basal medium and feed medium might have interrelated impacts on cell culture performance. Indeed, an improved basal medium can alter the metabolism and growth of cells, which then may require a modified feed. Therefore, sequential optimization of some elements has to be repeated, or sequential medium and feed optimization have to be followed by a final round of integrated optimization of feed and process settings, as proposed by Jiang Z et al. (2012) BioProcess International, 10:40-45.
Other groups have focused on the development of supplement blends. For instance, WO 12/078270 discloses screening methods to determine cell culture media supplements or supplement blends with enhanced performance characteristics. It describes, in particular, a supplement or combination of supplements comprising one, two or more components, to be added to culture media, case by case.
Numerous documents have described mammalian cell culture media. For instance, the application EP 2154244 discloses media for culturing cells, the media having at least 1 mM serine, at least 1 mM tyrosine and at least 0.4 mM cysteine. This application is silent with regard to the specific concentrations of the other components needed to obtain an optimized culture medium. The patent, EP481791, is related to culture media free from protein, lipid and carbohydrate isolated from an animal source, but instead uses recombinant protein sources, for instance, recombinant insulin. In addition, this patent discloses specific ranges of concentrations for the amino acids to be included in the culture media. Another example is U.S. Pat. No. 6,048,728, which describes a culture medium comprising at least one of glutamine, glutamate and asparagine at a concentration of at least 8 mM, tryptophan, another amino acid, and phospholipid precursors comprising at least choline and ethanolamine. Still another example is WO 98/45411, which discloses culture media with specific amino acid concentrations.
However, there is still a need to develop high performing processes in a minimal time frame to meet increasing market demands and reduce manufacturing costs. Developing high performing processes implicitly means developing high performing culture media, having no risk of contamination (i.e., being serum- and protein-free).